Polymer self-assembly has continually attracted interest because of the bottom-up control over order and the need to cheaply manufacture smaller structures, with applications including nanolithography, organic electronics, and biomaterials. Block copolymers are a canonical system for self-assembly, and there is a wide understanding of the thermodynamics of equilibrium nanostructures. However, the dynamic mechanisms of self-assembly are much less understood, and these become increasingly important as researchers pursue increasingly advanced applications that demand defect-free long-range order, or incorporate functional domains such as semiconducting polymers or proteins. This proposal explores optimal processing pathways for self-assembled block copolymer nanostructures using single-molecule super-resolution optical microscopy. This method enables in situ real space imaging at resolutions of &lt;25 nm, providing significant advantages over classical techniques such as time-resolved scattering which requires model fitting in Fourier space, or time-lapse AFM which only gives 2D information. Our work will focus on solvent vapor annealing and shear alignment processes, which are difficult to explore using other known methods. These are commonly used to improve order in self-assembly, but optimization typically requires significant trial-and-error and heuristics, suggesting that the fundamental mechanisms are not well-understood. Single-molecule tracking will enable diffusion measurements at the nanoscale, which are necessary for tuning assembly kinetics. Imaging will reveal the assembly mechanisms and provide additional detail such as grain growth and the migration and annihilation of defects. Finally, while super-resolution has become widespread and established in the biological sciences, very few studies have applied the technique to materials systems. Thus, this study is an excellent opportunity to introduce the method to the polymer community.
|Effective start/end date||9/1/17 → 8/31/21|
- American Chemical Society Petroleum Research Fund (57962-DN17)
Explore the research topics touched on by this project. These labels are generated based on the underlying awards/grants. Together they form a unique fingerprint.